Designs and orchestrates multi-agent systems

Building agents · competency building-agents/orchestrates-agents

Taught in: the Building agents course

Draws on: Design patterns, Orchestration and multi-agent

Learning objectives

Picks a design pattern for a task and says why (base)

Claim	Why	Example
The learner names the pattern (single loop, reflection, plan-then-execute, and so on) and the property of the task that calls for it.	A pattern picked because it is interesting adds calls and failure modes without a reason to point to.	"The task has ten dependent steps and a wrong early step wastes the rest, so plan first, then execute the plan step by step."
The learner starts with the simplest pattern that could work and adds structure when the evaluation shows a need.	Each added pattern multiplies calls and cost, and the simple version is the baseline the complex one must beat.	A single tool-using loop handles 80 percent of the evaluation set, and the learner adds reflection only after measuring where it fails.
The learner can say what each pattern costs in calls, latency and money for their task.	Reflection doubles calls, planning adds a call per plan revision, and the budget decides whether that is affordable.	"Reflection adds one call per step; at twelve steps that is twice the latency, which the user-facing flow cannot take."

Served by: Plan everything first or react step by step, Writing the plan before taking the steps, Reasoning before each action, A second pass that critiques the first

Justifies the coordination cost of more than one agent (base)

Claim	Why	Example
Before adding a second agent, the learner names what the single agent cannot do: a context that does not fit, a tool set too large, a skill that needs a different prompt.	Most multi-agent designs are a single agent with more coordination cost and no new ability.	"One agent's context fills with the codebase before it reaches the task, so a scout agent summarizes the relevant files first."
The learner counts the coordination cost: extra calls, handoff messages, lost context at each boundary, and the failure modes of agents disagreeing.	Every boundary between agents is a place where information is dropped and a decision is made twice.	A three-agent design spends 40 percent of its tokens on handoffs, and the learner shows this before deciding.
The learner compares the multi-agent design against the single-agent baseline on the same evaluation set.	A design that feels better must be shown to be better on the tasks that matter.	The orchestrated version scores three points higher at twice the cost, so the learner keeps the single agent and notes where the three points came from.

Served by: Orchestration in code or by a model, What every extra agent costs

Composes patterns and names the failure modes of the composition (expert)

Claim	Why	Example
The learner draws the composition and names, at each junction, what passes across and what is lost.	Composition failures happen at the seams: a planner that does not see what the executor learned, a reflector without the original goal.	The plan-then-execute loop passes the plan to the executor but not the constraints, so the executor breaks a limit the planner knew about, and the learner fixes the handoff.
The learner names the failure modes the composition adds: loops between components, disagreement without a tiebreaker, cost multiplying.	Each pattern has known failures alone, and combining them adds new ones that are in neither.	A reflector that keeps asking for revisions and an executor that keeps complying produce an unbounded loop, so the learner adds a revision cap.
The learner tests the composition with faults injected at each boundary.	A composed system that has only seen happy paths has untested error handling at every seam.	The test returns an empty plan from the planner and a tool error from the executor and checks that the orchestrator stops and reports.

Served by: Orchestration in code or by a model, Plan everything first or react step by step

Alignment

Framework	Code	Asks	Objectives here
Ng, AI engineering skills map	Building and deploying AI applications	Build, evaluate, ship	picks-a-pattern, justifies-orchestration-cost, composes-patterns
Brilliant Coding with AI	BLD-4, BLD-5	Organize and oversee a workflow	picks-a-pattern